1 //===----------------------------------------------------------------------===// 2 // 3 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. 4 // See https://llvm.org/LICENSE.txt for license information. 5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception 6 // 7 //===----------------------------------------------------------------------===// 8 9 #ifndef _LIBCPP___RANDOM_POISSON_DISTRIBUTION_H 10 #define _LIBCPP___RANDOM_POISSON_DISTRIBUTION_H 11 12 #include <__config> 13 #include <__random/clamp_to_integral.h> 14 #include <__random/exponential_distribution.h> 15 #include <__random/is_valid.h> 16 #include <__random/normal_distribution.h> 17 #include <__random/uniform_real_distribution.h> 18 #include <cmath> 19 #include <iosfwd> 20 #include <limits> 21 22 #if !defined(_LIBCPP_HAS_NO_PRAGMA_SYSTEM_HEADER) 23 # pragma GCC system_header 24 #endif 25 26 _LIBCPP_PUSH_MACROS 27 #include <__undef_macros> 28 29 _LIBCPP_BEGIN_NAMESPACE_STD 30 31 template <class _IntType = int> 32 class _LIBCPP_TEMPLATE_VIS poisson_distribution { 33 static_assert(__libcpp_random_is_valid_inttype<_IntType>::value, "IntType must be a supported integer type"); 34 35 public: 36 // types 37 typedef _IntType result_type; 38 39 class _LIBCPP_TEMPLATE_VIS param_type { 40 double __mean_; 41 double __s_; 42 double __d_; 43 double __l_; 44 double __omega_; 45 double __c0_; 46 double __c1_; 47 double __c2_; 48 double __c3_; 49 double __c_; 50 51 public: 52 typedef poisson_distribution distribution_type; 53 54 _LIBCPP_HIDE_FROM_ABI explicit param_type(double __mean = 1.0); 55 56 _LIBCPP_HIDE_FROM_ABI double mean() const { return __mean_; } 57 58 friend _LIBCPP_HIDE_FROM_ABI bool operator==(const param_type& __x, const param_type& __y) { 59 return __x.__mean_ == __y.__mean_; 60 } 61 friend _LIBCPP_HIDE_FROM_ABI bool operator!=(const param_type& __x, const param_type& __y) { return !(__x == __y); } 62 63 friend class poisson_distribution; 64 }; 65 66 private: 67 param_type __p_; 68 69 public: 70 // constructors and reset functions 71 #ifndef _LIBCPP_CXX03_LANG 72 _LIBCPP_HIDE_FROM_ABI poisson_distribution() : poisson_distribution(1.0) {} 73 _LIBCPP_HIDE_FROM_ABI explicit poisson_distribution(double __mean) : __p_(__mean) {} 74 #else 75 _LIBCPP_HIDE_FROM_ABI explicit poisson_distribution(double __mean = 1.0) : __p_(__mean) {} 76 #endif 77 _LIBCPP_HIDE_FROM_ABI explicit poisson_distribution(const param_type& __p) : __p_(__p) {} 78 _LIBCPP_HIDE_FROM_ABI void reset() {} 79 80 // generating functions 81 template <class _URNG> 82 _LIBCPP_HIDE_FROM_ABI result_type operator()(_URNG& __g) { 83 return (*this)(__g, __p_); 84 } 85 template <class _URNG> 86 _LIBCPP_HIDE_FROM_ABI result_type operator()(_URNG& __g, const param_type& __p); 87 88 // property functions 89 _LIBCPP_HIDE_FROM_ABI double mean() const { return __p_.mean(); } 90 91 _LIBCPP_HIDE_FROM_ABI param_type param() const { return __p_; } 92 _LIBCPP_HIDE_FROM_ABI void param(const param_type& __p) { __p_ = __p; } 93 94 _LIBCPP_HIDE_FROM_ABI result_type min() const { return 0; } 95 _LIBCPP_HIDE_FROM_ABI result_type max() const { return numeric_limits<result_type>::max(); } 96 97 friend _LIBCPP_HIDE_FROM_ABI bool operator==(const poisson_distribution& __x, const poisson_distribution& __y) { 98 return __x.__p_ == __y.__p_; 99 } 100 friend _LIBCPP_HIDE_FROM_ABI bool operator!=(const poisson_distribution& __x, const poisson_distribution& __y) { 101 return !(__x == __y); 102 } 103 }; 104 105 template <class _IntType> 106 poisson_distribution<_IntType>::param_type::param_type(double __mean) 107 // According to the standard `inf` is a valid input, but it causes the 108 // distribution to hang, so we replace it with the maximum representable 109 // mean. 110 : __mean_(isinf(__mean) ? numeric_limits<double>::max() : __mean) { 111 if (__mean_ < 10) { 112 __s_ = 0; 113 __d_ = 0; 114 __l_ = std::exp(-__mean_); 115 __omega_ = 0; 116 __c3_ = 0; 117 __c2_ = 0; 118 __c1_ = 0; 119 __c0_ = 0; 120 __c_ = 0; 121 } else { 122 __s_ = std::sqrt(__mean_); 123 __d_ = 6 * __mean_ * __mean_; 124 __l_ = std::trunc(__mean_ - 1.1484); 125 __omega_ = .3989423 / __s_; 126 double __b1 = .4166667E-1 / __mean_; 127 double __b2 = .3 * __b1 * __b1; 128 __c3_ = .1428571 * __b1 * __b2; 129 __c2_ = __b2 - 15. * __c3_; 130 __c1_ = __b1 - 6. * __b2 + 45. * __c3_; 131 __c0_ = 1. - __b1 + 3. * __b2 - 15. * __c3_; 132 __c_ = .1069 / __mean_; 133 } 134 } 135 136 template <class _IntType> 137 template <class _URNG> 138 _IntType poisson_distribution<_IntType>::operator()(_URNG& __urng, const param_type& __pr) { 139 static_assert(__libcpp_random_is_valid_urng<_URNG>::value, ""); 140 double __tx; 141 uniform_real_distribution<double> __urd; 142 if (__pr.__mean_ < 10) { 143 __tx = 0; 144 for (double __p = __urd(__urng); __p > __pr.__l_; ++__tx) 145 __p *= __urd(__urng); 146 } else { 147 double __difmuk; 148 double __g = __pr.__mean_ + __pr.__s_ * normal_distribution<double>()(__urng); 149 double __u; 150 if (__g > 0) { 151 __tx = std::trunc(__g); 152 if (__tx >= __pr.__l_) 153 return std::__clamp_to_integral<result_type>(__tx); 154 __difmuk = __pr.__mean_ - __tx; 155 __u = __urd(__urng); 156 if (__pr.__d_ * __u >= __difmuk * __difmuk * __difmuk) 157 return std::__clamp_to_integral<result_type>(__tx); 158 } 159 exponential_distribution<double> __edist; 160 for (bool __using_exp_dist = false; true; __using_exp_dist = true) { 161 double __e; 162 if (__using_exp_dist || __g <= 0) { 163 double __t; 164 do { 165 __e = __edist(__urng); 166 __u = __urd(__urng); 167 __u += __u - 1; 168 __t = 1.8 + (__u < 0 ? -__e : __e); 169 } while (__t <= -.6744); 170 __tx = std::trunc(__pr.__mean_ + __pr.__s_ * __t); 171 __difmuk = __pr.__mean_ - __tx; 172 __using_exp_dist = true; 173 } 174 double __px; 175 double __py; 176 if (__tx < 10 && __tx >= 0) { 177 const double __fac[] = {1, 1, 2, 6, 24, 120, 720, 5040, 40320, 362880}; 178 __px = -__pr.__mean_; 179 __py = std::pow(__pr.__mean_, (double)__tx) / __fac[static_cast<int>(__tx)]; 180 } else { 181 double __del = .8333333E-1 / __tx; 182 __del -= 4.8 * __del * __del * __del; 183 double __v = __difmuk / __tx; 184 if (std::abs(__v) > 0.25) 185 __px = __tx * std::log(1 + __v) - __difmuk - __del; 186 else 187 __px = __tx * __v * __v * 188 (((((((.1250060 * __v + -.1384794) * __v + .1421878) * __v + -.1661269) * __v + .2000118) * __v + 189 -.2500068) * 190 __v + 191 .3333333) * 192 __v + 193 -.5) - 194 __del; 195 __py = .3989423 / std::sqrt(__tx); 196 } 197 double __r = (0.5 - __difmuk) / __pr.__s_; 198 double __r2 = __r * __r; 199 double __fx = -0.5 * __r2; 200 double __fy = __pr.__omega_ * (((__pr.__c3_ * __r2 + __pr.__c2_) * __r2 + __pr.__c1_) * __r2 + __pr.__c0_); 201 if (__using_exp_dist) { 202 if (__pr.__c_ * std::abs(__u) <= __py * std::exp(__px + __e) - __fy * std::exp(__fx + __e)) 203 break; 204 } else { 205 if (__fy - __u * __fy <= __py * std::exp(__px - __fx)) 206 break; 207 } 208 } 209 } 210 return std::__clamp_to_integral<result_type>(__tx); 211 } 212 213 template <class _CharT, class _Traits, class _IntType> 214 _LIBCPP_HIDE_FROM_ABI basic_ostream<_CharT, _Traits>& 215 operator<<(basic_ostream<_CharT, _Traits>& __os, const poisson_distribution<_IntType>& __x) { 216 __save_flags<_CharT, _Traits> __lx(__os); 217 typedef basic_ostream<_CharT, _Traits> _OStream; 218 __os.flags(_OStream::dec | _OStream::left | _OStream::fixed | _OStream::scientific); 219 return __os << __x.mean(); 220 } 221 222 template <class _CharT, class _Traits, class _IntType> 223 _LIBCPP_HIDE_FROM_ABI basic_istream<_CharT, _Traits>& 224 operator>>(basic_istream<_CharT, _Traits>& __is, poisson_distribution<_IntType>& __x) { 225 typedef poisson_distribution<_IntType> _Eng; 226 typedef typename _Eng::param_type param_type; 227 __save_flags<_CharT, _Traits> __lx(__is); 228 typedef basic_istream<_CharT, _Traits> _Istream; 229 __is.flags(_Istream::dec | _Istream::skipws); 230 double __mean; 231 __is >> __mean; 232 if (!__is.fail()) 233 __x.param(param_type(__mean)); 234 return __is; 235 } 236 237 _LIBCPP_END_NAMESPACE_STD 238 239 _LIBCPP_POP_MACROS 240 241 #endif // _LIBCPP___RANDOM_POISSON_DISTRIBUTION_H 242